International conflict and strategic games

Abstract

The pervasiveness of international conflict makes of it one of the main topics of discussion among IR scholars. The discipline has extensively attempted to model the conditions and settings under which armed conflict emerges, at sometimes resorting to formal models as tools to generate hypotheses and predictions. In this paper, I analyse two distinct approaches to formal modelling in IR: one that fits data into mathematical models and another that derives statistical equations directly from a model’s assumption. In doing so, I raise the following question: how should maths and stats be linked in order to consistently test the validity of formal models in IR? To answer this question, I scrutinise James Fearon’s audience costs model and Curtis Signorino’s strategic interaction game, highlighting their mathematical assumptions and implications to testing formal models. I argue that Signorino’s approach offer a more consistent set of epistemological and methodological tools to model testing, for it derives statistical equations that respect a model’s assumptions, whereas the data-fit approach tends to ignore such considerations.